Paul wavelet algorithm for the determination of birefringence dispersion of a liquid crystal cell

Coşkun, Emre; Özder, Serhat

doi:10.1364/josab.28.002974

Cited by 9 publications

(5 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In our study Paul wavelet is chosen as the mother wavelet because of the varying parameter, and its analyzing wavelet form in Fourier domain is given as (Coşkun & Özder, 2011),

\overset{Ψ}{true} ((), aα) = \frac{2^{m}}{{([], m ((), 2 m - 1)!)}^{1 / 2}} {(italicaα)}^{m} \exp ((), - italicaα) ξ ((), aα),

where ξ ( α ) is the Heaviside step function, m is the varying parameter which affect the resolution on x and α domains, and this property has an important role for the analysis (Coşkun & Özder, 2011).…”

Section: Methodsmentioning

confidence: 99%

“…In our study Paul wavelet is chosen as the mother wavelet because of the varying parameter, and its analyzing wavelet form in Fourier domain is given as (Coşkun & Özder, 2011),…”

Section: Phase Calculation For Surface Profile Measurementmentioning

confidence: 99%

“…where ξ(α) is the Heaviside step function, m is the varying parameter which affect the resolution on x and α domains, and this property has an important role for the analysis (Coşkun & Özder, 2011).…”

Section: Phase Calculation For Surface Profile Measurementmentioning

confidence: 99%

“…However, Paul wavelet has the ability to control the resolution of the analyzing wavelet by the variable parameter. Because of this degree of freedom, Paul wavelet can better detect the local characteristics of the fringe pattern, which results in precise measurement (Coşkun & Özder, 2011; Coşkun, Özder, & Tiryaki, 2013). Hence, Paul wavelet has the better precision with the variable parameter.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Quantitative phase imaging of erythrocyte in epilepsy patients

Ünal

Kocahan

Altunan

et al. 2020

Microscopy Res & Technique

Self Cite

View full text Add to dashboard Cite

The present study focuses on the quantitative phase imaging of erythrocytes with the aim to compare the morphological differences between epilepsy patients under antiepileptic treatment, who have no other disease which may affect the erythrocyte morphology, and the healthy control group. The white light diffraction phase microscopy (WDPM) has been used to obtain the interferogram of the erythrocyte surfaces.The continuous wavelet transform with Paul wavelet has been chosen to calculate the surface profiles from this interferogram image. For the determination of alteration in morphology, besides WDPM, erythrocyte surfaces have been investigated by light microscope and scanning electron microscope. In this way, it has been possible to see the difference in terms of precision and implementation between the most commonly used methods with regard to the quantitative phase imaging. Erythrocytes from all the samples have been examined and displayed in both two-and threedimensional way. We have observed that erythrocytes of patients with effective antiepileptic blood levels were more affected in morphology than healthy subjects. When we compared the erythrocyte morphological changes of patients who received monotherapy or polytherapy, no difference was observed. In conclusion, antiepileptic drugs (AEDs) cause red blood cell (RBC) morphological changes and a combined usage of WDPM with Paul wavelet and light microscopy methods are very convenient for studying the erythrocyte morphologies on multiple patients.

show abstract

“…In our study Paul wavelet is chosen as the mother wavelet because of the varying parameter, and its analyzing wavelet form in Fourier domain is given as (Coşkun & Özder, 2011),

\overset{Ψ}{true} ((), aα) = \frac{2^{m}}{{([], m ((), 2 m - 1)!)}^{1 / 2}} {(italicaα)}^{m} \exp ((), - italicaα) ξ ((), aα),

Section: Methodsmentioning

confidence: 99%

“…In our study Paul wavelet is chosen as the mother wavelet because of the varying parameter, and its analyzing wavelet form in Fourier domain is given as (Coşkun & Özder, 2011),…”

Section: Phase Calculation For Surface Profile Measurementmentioning

confidence: 99%

Section: Phase Calculation For Surface Profile Measurementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Quantitative phase imaging of erythrocyte in epilepsy patients

Ünal

Kocahan

Altunan

et al. 2020

Microscopy Res & Technique

Self Cite

View full text Add to dashboard Cite

show abstract

“…Morlet wavelet has a single degree of freedom, controlled by a fixed spatial frequency, which is chosen to be about 5 or 6 (1/pixel) to satisfy the admissibility condition. Unlike Morlet wavelet, Paul wavelet has the ability to control the resolution of the analyzing wavelet by the degree of Paul wavelet [22,23]. Generalized morse wavelets (GMW) were introduced as the eigen functions of a time-frequency localization operator [24,25].…”

Section: Introductionmentioning

confidence: 99%

Determination of phase from the ridge of CWT using generalized Morse wavelet

Kocahan¹,

Tiryaki²,

Coşkun³

et al. 2018

Meas. Sci. Technol.

View full text Add to dashboard Cite

The selection of wavelet is an important step in order to determine the phase from the fringe patterns. In the present work, a new wavelet for phase retrieval from the ridge of continuous wavelet transform (CWT) is presented. The phase distributions have been extracted from the optical fringe pattern by choosing the zero order generalized morse wavelet (GMW) as a mother wavelet. The aim of the study is to reveal the ways in which the two varying parameters of GMW affect the phase calculation. To show the validity of this method, an experimental study has been conducted by using the diffraction phase microscopy (DPM) setup; consequently, the profiles of red blood cells have been retrieved. The results for the CWT ridge technique with GMW have been compared with the results for the Morlet wavelet and the Paul wavelet; the results are almost identical for Paul and zero order GMW because of their degree of freedom. Also, for further discussion, the Fourier transform and the Stockwell transform have been applied comparatively. The outcome of the comparison reveals that GMWs are highly applicable to the research in various areas, predominantly biomedicine.

show abstract